Search Results for "itk-snap medical image segmentation tool mac"

An open-source convolutional neural networks platform for medical image analysis and image-guided therapy. NiftyNet is a TensorFlow-based open-source convolutional neural networks (CNNs) platform for research in medical image analysis and image-guided therapy. NiftyNet’s modular structure is designed for sharing networks and pre-trained models. Using this modular structure you can get started with established pre-trained networks using built-in tools. Adapt existing networks to your imaging...

Deep-Learning-for-Medical-Applications is a repository that compiles deep learning methods, code implementations, and examples applied to medical imaging and healthcare data. The project addresses domain-specific challenges like segmentation, classification, detection, and multimodal data (e.g. MRI, CT, X-ray) using state-of-the-art architectures (e.g. U-Net, ResNet, GAN variants) tailored to medical constraints (small datasets, annotation costs, class imbalance). It includes Jupyter...

The MatrixUser project is moving to GitHub, the latest version can be obtained from https://leoliuf.github.io/MatrixUser/ Most of the medical images (e.g. CT, MRI, PET, etc.) comprises multiple frames which represent slices, phases, timing etc. from the same imaging object. Those images can be saved as multidimensional matrices in Matlab thanks to Matlab's powerful support of multidimensional data representation. However, within Matlab, most of image manipulation functions are limited or...